The present invention relates generally to methods and apparatus for collecting medical data, and for providing a patient with customized access to the data. More specifically, the present invention provides a computerized profiler system for building a medical database from medical literature, and automatically generating personalized profiles based on information provided by a patient and medical data stored in the medical database.
As medical information resources have become easier to access, the public demand for such resources has increased. The Internet has enabled millions of users worldwide to access an ever-growing selection of medical information, and has resulted in patients becoming increasingly knowledgeable about their medical conditions. Additionally, the Internet has provided patients with access to world-wide on-line communities of individuals with similar medical conditions, who are able to share their experiences and advice.
While this increase in the availability of medical information to patients has had some good effects, such as a heightened level of discussion between physicians and patients, it also has some drawbacks. Much of the information available to patients over the Internet is unreliable. It is often based on individual experiences or opinions, rather than on solid medical research. Such material can mislead patients, or even cause additional medical difficulties if unreliable advice is followed without first consulting a physician.
Even medical information provided by reliable on-line sources may not be helpful. Much of the information that is available is highly technical, and is not comprehensible to most patients. Reliable information that is written for use by patients who do not have extensive medical knowledge is often too general to be useful, and may not include information on the latest research and treatments. Additionally, almost all of the information available to patients over the Internet is generic, in that it is not specifically tailored to the individual patient""s medical conditions.
At the same time that patients are gaining access to medical information, medical knowledge is growing at an ever increasing rate. Each month, dozens of studies on a variety of diseases and treatments are published in numerous credible medical journals. The volume of information published each year on some major diseases, such as cancer, is becoming so great that even specialists in the field may be unable to keep up with all the latest research. Without knowledge of the latest research and techniques, a physician may not be able to render the best possible advice to his or her patients.
This difficulty in rendering the best advice is further compounded by the fact that many patients are becoming more sophisticated in the demands that they place on physicians, as discussed above. Physicians may have difficulty keeping up with the latest information that will be required to satisfy knowledgeable patients, who may have detailed questions pertaining to recent research and techniques.
There have been many attempts to provide automated systems for generating individualized medical diagnoses or advice. A couple of recent examples are shown in U.S. Pat. No. 5,711,297, to Iliff, which provides automated medical advise to the general public over a telephone, and U.S. Pat. No. 5,724,580, to Levin et al., which assists physicians by automatically generating individualized management and prognosis reports.
Typically, these systems ask the patient (or physician) a series of questions, or require that data about a patient""s condition be entered into a computer. This information is processed by applying a set of rules to the data, which results in the system generating diagnoses or advice.
One difficulty with such systems is that the rules are often static, and are based on the knowledge of one or more physicians, or gleaned from medical textbooks on the field to which the rules pertain. Thus, the rules depend on the specific knowledge of a few individuals, or on general medical knowledge, rather than being based on the latest research. Since the rules tend to be static, either contained in a database of rules or hard-coded into the system, it may be difficult to update the rules based on new research.
Even in systems where the rules are not static, there is no way of entering the results of the latest medical research, other than updating the rules. Since the rules in these systems are typically complex and interrelated, a change in one rule may lead to many changes in the rule base. Thus, changing a few rules to account for the latest research may lead to many changes in the rules on which a system operates.
A few systems have rejected a rules-based approach, in favor of a more dynamic method. U.S. Pat. No. 5,586,024, to Shaibani, for example, matches accident factors for a current patient against accident factors from past accidents to diagnose possible trauma injuries. By basing a diagnosis on past results, this approach permits the system to be automatically updated based on its most recent experiences. Since the system is not rule-based, it is not necessary to derive and enter a complex set of rules. However, because the (system described in Shaibani depends on experience, rather than knowledge, reports generated by the system are not based on medical research.
Both rules-based systems and those that use some other approach typically focus on providing a medical diagnosis or medical advice, rather than on providing medical information. Rather than attempting to augment the patient""s or physician""s knowledge, most known systems attempt to replace or augment a physician""s judgement in making a diagnosis. For example, most systems do not provide citations to medical papers that may be helpful or relevant to the individual patient or his/her physician.
In view of the above, it would be desirable to provide an automated system that generates individualized medical information for a patient based on information provided by the patient, and on knowledge extracted from medical research literature.
It would further be desirable to provide methods and structures for extracting and storing useful results or other information from medical literature.
It also would be desirable to provide automated methods for applying medical knowledge stored in a medical database to provide a patient with individualized information on a variety of treatment options that may be discussed with a physician.
It is an object of the present invention to provide an automated system that generates individualized medical information for a patient based on information provided by the patient, and on knowledge extracted from medical research literature.
It is a further object of the present invention to provide methods and structures for extracting and storing useful results or other information from medical literature.
It also is an object of the present invention to provide automated methods for applying medical knowledge stored in a medical database to provide a patient with individualized information on a variety of treatment options that may be discussed with a physician.
These and other objects of the present invention are achieved by providing a system that stores information extracted from medical literature in a medical database, and uses the information in the database, along with information provided by a patient, to generate an individualized medical profile, containing information on available treatments, as well as information on the medical literature that was used to generate the treatment information.
In a preferred embodiment of the system of the present invention, a medical database is stored on a server computer, and patients interact with the server computer over the Internet. A user connects to the system over the Internet using a standard web browser, and interacts with the system by filling out one or more forms that request specific information from the user. The system then uses a medical database, built using information from the medical literature, to generate an individualized profile for the patient. In a preferred embodiment, the individualized profile is displayed in the web browser, and the patient may select links in the individualized profile to access more detailed information on the medical literature that was used to generate the profile.
The system of the present invention includes two major components: extraction of information from medical literature to build a medical database; and a series of programmed routines that use the medical database, along with information provided by a patient, to generate an individualized profile.
Preferably, an editorial review board made up of specialists in numerous medical fields is assembled to review and score medical literature for inclusion in the medical database. Based on predetermined criteria, the review board determines which papers and studies should be used to generate a database of medical information for a specific disease state, e.g., prostate cancer. The review board continually evaluates new medical literature, and adds new studies to the medical database. In this way, the information in the medical database is continually updated to reflect the latest research.
Studies that are accepted for inclusion in the database go through a data extraction process in which useful information and algorithms from the papers are extracted and stored in various tables in the medical database. Input parameters, output parameters, data tables, information on the study population, statistical information, and any appropriate algorithms employed in the paper, together with an abstract, and citation information are extracted from each study. Additionally, each study is assigned an output category, based on the function served by the output of the study, a treatment category, based on the treatment applied in the study, and a combination rule, which is used to combine output from the study into xe2x80x9csuper-categoriesxe2x80x9d. All of this information, as well as information on available treatments and their indications are stored in the medical database.
The second component of the system comprises a series of programmed routines constructed in accordance with the present invention that use the medical database to generate customized profiles for patients. A patient provides various personal and clinical information to the system as input. If there is any missing information, the system provides a missing information report to the patient. Next, the database is used to match the available information against the input parameters for each of the studies in the medical database. Algorithms or tables extracted from all studies for which the input parameters were matched are applied to the information provided by the patient to generate output data. Combination analysis is then performed on the output data to combine the output from the various studies into predetermined xe2x80x9csuper-categoryxe2x80x9d values.
Next, information on treatments and their indications stored in the medical database is applied to the information provided by the patient, and to the xe2x80x9csuper-categoryxe2x80x9d values, to determine which treatments are most applicable. For each of the treatments, the information provided by the patient, as well as the combined xe2x80x9csuper-categoryxe2x80x9d values, and the output from the studies are used in conjunction with the studies in the medical database that pertain to the outcome of the treatment to generate information on the probable outcome of each treatment.
All of the information on the input provided by the patient, the output data from the studies, the xe2x80x9csuper-categoryxe2x80x9d values, the indicated treatments, the probable treatment outcomes, and the studies that were applied are combined to generate a personalized profile. The personalized profile is then made available to the patient. The patient is advised to discuss the profile with a physician, who may be able to assist the patient in assessing the profile, and may provide additional information to the system. As the patient adds or changes the input data, the system may be employed to generate updated personal profiles.